Streaming Graph Processing on Categorical Data Enables Real-time Risk Calculation

thatDot avatar thatDot

The failure of Silicon Valley Bank in 2023 exemplifies the severe consequences of not accurately assessing risk in a timely manner. Although nearly every financial institution prioritizes risk minimization, their methods for calculating risk often rely on detailed analysis of categorical data and relationships. Most existing algorithms, however, only handle static, numeric data. This requires transforming the data, typically through methods like one-hot encoding, into numerical formats that are bulky, sparse, and slow to process. After analysis, the data often needs to be converted back to its original categories, adding to the inefficiency. Current state-of-the-art solutions take hours to deliver insights.

If we could perform this analysis earlier in the process, using the original categorical data as it streams in without modification, we could reduce the mean time to insight to seconds, potentially saving financial institutions significant amounts of money. This approach could also enable new capabilities, such as using graph NLP on streaming data to identify novel behaviors and detect anomalies like cyber-attacks before they impact systems. The combination of fast, in-line data processing engines like Flink or KsqlDB with graph algorithms and categorical analysis is exceptionally powerful. Join us to learn about a new open-source streaming intelligence system that revolutionizes risk analysis and other fast categorical data processing.

Event Details:

Title: Streaming Graph Processing on Categorical Data Enables Real-time Risk Calculation

Date: July 12, 2024

Time: 10:45am – 11:20am ET

thatDot's Paige Roberts speaking at Data Connect on July 12, 2024

Why You Should Attend

Attending Paige’s speech at Data Connect 2024 is a must for anyone serious about staying at the forefront of data science and risk management. Paige will unveil groundbreaking techniques for real-time risk analysis, demonstrating how to cut mean time to insight from hours to seconds. This shift can save financial institutions substantial costs and enhance their ability to detect anomalies, including cyber-attacks, before they cause harm. Paige will explore the synergy of in-line data processing engines like Flink or KsqlDB with advanced graph algorithms and categorical analysis. By attending, you’ll gain invaluable insights into innovative data processing methods that can revolutionize your organization’s approach to risk and data management. Don’t miss this opportunity to learn from a leading expert and enhance your strategic capabilities in the evolving data landscape.